Development and Validation of a Prediction Model for Organ-Specific Recurrences After Curative Resection of Colon Cancer

BACKGROUND: Early detection of postoperative recurrence is beneficial for patients with cancer; however, optimal surveillance remains an issue. To optimize the follow-up plan, the estimation of an individual patient's risk of recurrence is indispensable.

OBJECTIVE: This study aimed to establish a statistical model for predicting the risk of organ-specific recurrence after curative resection of colon cancer.

DESIGN: This was a retrospective cohort study at a tertiary referral hospital.

SETTINGS: This study included 1720 patients with colon cancer treated at the University of Tokyo Hospital between 1997 and 2015. Data were retrospectively retrieved from patient medical charts. The risk score was developed using a competing risk model in a derivation cohort (973 patients treated in 1997-2009) and then validated in a validation cohort (747 patients treated in 2010-2015).

PATIENTS: Patients who underwent curative resection for stage I to III colon cancer were included.

MAIN OUTCOME MEASURES: The prediction of the incidence of postoperative liver and lung metastasis of colon cancer was measured.

LIMITATIONS: The generalizability of the model to different healthcare settings remains to be elucidated.

CONCLUSIONS: We developed a prediction model to estimate the risk of recurrence in the liver and lung after curative resection of colon cancer, which demonstrated good discrimination ability in the external validation cohort. Our model can aid clinicians and patients in customizing postoperative surveillance according to an individual patient's risk of organ-specific recurrence. See Video Abstract at http://links.lww.com/DCR/A977.